Args:
    data_path: Path to data file or directory
    data_type: 'visium', 'xenium', 'slide_seq', 'merfish', 'seqfish', or 'generic'
    name: Optional dataset name

Returns:
    SpatialDataset with cell/gene counts and metadata profiles

This tool does not compute PCA, UMAP, clustering, or neighbor graphs. Run
compute_embeddings() afterward when downstream tools require those artifacts.

Args:
    data_id: Dataset ID
    params: Preprocessing parameters (all have sensible defaults)

Args:
    data_id: Dataset ID
    params: Embedding parameters (PCA, UMAP, clustering, etc.)

Args:
    data_id: Dataset ID
    params: Visualization parameters (plot_type, subtype, genes, output_format, dpi, etc.)

Args:
    data_id: Dataset ID
    params: Annotation parameters (method, reference_data_id, cell_type_key, etc.)

Note: Reference methods (tangram, scanvi) require reference_data_id to be preprocessed first.
Rule-based methods: marker_score labels the groups of cluster_label (e.g. spatial
domains) by mean log-normalized marker expression; threshold labels observations
by a cutoff on a numeric obs column (e.g. deconvolution_rctd_<cell type>).
Both write to output_key.

Args:
    data_id: Dataset ID
    params: Analysis parameters (analysis_type, cluster_key, genes). See SpatialStatisticsParameters for all types.

gene_selection='all' computes moran/geary for every gene; the full per-gene
table (rank, statistic, p, FDR) is stored at results_key, only top genes are returned.

Args:
    data_id: Dataset ID
    params: Required - group_key and optional method, group1/group2, n_top_genes, etc.

Args:
    data_id: Dataset ID
    params: Required - condition_key, condition1, condition2, sample_key, etc.

Args:
    data_id: Dataset identifier
    params: Required - reference_key, reference_categories, and optional method/thresholds.

Gene positions missing from adata.var are annotated from bundled Ensembl 110
tables (species: human GRCh38 or mouse GRCm39). exclude_gene_classes removes
immunoglobulin, ribosomal, mitochondrial or HLA genes from the CNV input;
query_categories restricts CNV clustering to those reference_key categories.

Args:
    data_id: Dataset ID
    params: Velocity parameters (method, scvelo_mode, etc.)

Args:
    data_id: Dataset ID
    params: Trajectory parameters (method, root_cell, spatial_weight, etc.)

Args:
    data_ids: List of dataset IDs to integrate
    params: Integration parameters (method, batch_key, n_pcs, etc.)

batch_correction=False pools the samples without correction (shared genes,
counts in layers['counts'], obs and coordinates kept), e.g. to pool sections
for analyze_cell_communication.

Args:
    data_id: Dataset ID
    params: Required - method, cell_type_key, reference_data_id. See DeconvolutionParameters for all methods and options.

Args:
    data_id: Dataset ID
    params: Spatial domain parameters (method, n_domains, resolution, etc.)

Args:
    data_id: Dataset ID
    params: Required - species, cell_type_key, and method. For mouse with liana, set liana_resource='mouseconsensus'.

subset_key + subset_categories restrict the analysis to those observations
(e.g. tc_le_region in ['TC', 'LE']).

Args:
    data_id: Dataset ID
    params: Required - species must be specified. See EnrichmentParameters for methods and gene_set_database options.

Args:
    data_id: Dataset ID
    params: Spatial variable gene parameters (method, n_top_genes, etc.)

Args:
    source_id: Source dataset ID
    target_id: Target dataset ID to align to
    params: Registration parameters (method, alignment settings, etc.)

Returns:
    Registration result with method, dataset IDs, spot counts, and registered spatial key

Args:
    data_id: Dataset ID to export
    path: Custom path (default: ~/.chatspatial/active/{data_id}.h5ad)

Returns:
    Absolute path where data was exported

Args:
    data_id: Dataset ID to reload (must exist in MCP memory)
    path: Custom path (default: ~/.chatspatial/active/{data_id}.h5ad)

Returns:
    Summary of reloaded dataset